Sensitivity of WRF to driving data and physics options on a seasonal time-scale for the southwest of Western Australia

Kala, Jatin; Andrys, Julia; Lyons, Thomas; Foster, Ian; Evans, Bradley J.

doi:10.1007/s00382-014-2160-2

Cited by 62 publications

(61 citation statements)

References 73 publications

(101 reference statements)

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“…A 3-month model spinup period was used. The model setup and parameter options that were chosen by Andrys et al (2015Andrys et al ( , 2016Andrys et al ( , 2017 were based on the findings of Kala et al (2015), who explored the sensitivity of WRF to different physics options and input forcing data over SWWA. The setup included the single-moment 5-class microphysics scheme (Hong et al 2004), the Rapid Radiative Transfer Model for longwave radiation (Mlawer et al 1997), the Dudhia scheme for shortwave radiation (Dudhia 1989), the Yonsei University planetary boundary layer scheme (Hong and Lim 2006), the Kain-Fritsch (Kain 2004) scheme for convective parameterization for the first (50 km) and second (10 km) domains only, the MM5 surface-layer scheme (Grell et al 2000), and the Noah land surface model (Chen and Dudhia 2001).…”

Section: B Climate Model Datamentioning

confidence: 99%

“…1), have been conducted by Kala et al (2015) and Andrys et al (2015Andrys et al ( , 2016Andrys et al ( , 2017 using the Weather Research and Forecasting (WRF) Model. WRF is a next-generation mesoscale modeling system (Skamarock et al 2005) that has been commonly used for the purposes of dynamically downscaling GCMs, including applications in Europe (Heikkilä et al 2011;Soares et al 2012), North America (Gula and Peltier 2012), Asia (Chotamonsak et al 2011;En-Tao et al 2010), and eastern Australia (Evans and McCabe 2010).…”

Section: Introductionmentioning

confidence: 99%

“…WRF, like any RCM, is sensitive to model physics options as well as the input forcing data, and this sensitivity was assessed by Kala et al (2015) over SWWA at a 10-km resolution over a 1-yr time scale. They found that the ERA-Interim (Dee et al 2011) was the bestperforming reanalysis for the region as compared with the NCEP-NCAR reanalysis (Kalnay et al 1996) and NCEP's final (FNL) global tropospheric reanalysis, and they also determined the best combination of WRF physics options (among some of the most commonly used options) for SWWA.…”

Section: Introductionmentioning

confidence: 99%

“…Based on the findings of Kala et al (2015), Andrys et al (2015) used the same model setup of Kala et al (2015) but extended the simulations over a 30-yr period (1981-2010) using ERA-Interim. Two nested domains at 5-and 10-km resolutions were evaluated.…”

Section: Introductionmentioning

confidence: 99%

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An Analysis of Regional Climate Simulations for Western Australia’s Wine Regions—Model Evaluation and Future Climate Projections

Firth

Kala

Lyons

et al. 2017

Journal of Applied Meteorology and Climatology

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The Weather Research and Forecasting (WRF) Model is evaluated as a regional climate model for the simulation of climate indices that are relevant to viticulture in Western Australia's wine regions at a 5-km resolution under current and future climate. WRF is driven with ERA-Interim reanalysis for the current climate and three global climate models (GCMs) for both current and future climate. The focus of the analysis is on a selection of climate indices that are commonly used in climate-viticulture research. Simulations of current climate are evaluated against an observational dataset to quantify model errors over the 1981-2010 period. Changes to the indices under future climate based on the SRES A2 emissions scenario are then assessed through an analysis of future (2030-59) minus present climate. Results show that when WRF is driven with ERA-Interim there is generally good agreement with observations for all of the indices although there is a noticeable negative bias for the simulation of precipitation. The results for the GCMforced simulations were less consistent. Namely, while the GCM-forced simulations performed reasonably well for the temperature indices, all simulations performed inconsistently for the precipitation index. Climate projections showed significant warming for both of the temperature indices and indicated potential risks to Western Australia's wine growing regions under future climate, particularly in the north. There was disagreement between simulations with regard to the projections of the precipitation indices and hence greater uncertainty as to how these will be characterized under future climate.

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Section: B Climate Model Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Analysis of Regional Climate Simulations for Western Australia’s Wine Regions—Model Evaluation and Future Climate Projections

Firth

Kala

Lyons

et al. 2017

Journal of Applied Meteorology and Climatology

Self Cite

View full text Add to dashboard Cite

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“…A coarse comparison of the two datasets did not reveal substantial differences in WRF output. Kala et al (2015) show and state that the use of ERA-Interim and FNL is appropriate for re-producing the past climate as accurately as possible.…”

Section: Initial and Boundary Conditionsmentioning

confidence: 96%

A bias corrected WRF mesoscale fire weather dataset for Victoria, Australia 1972-2012

Brown¹,

Mills²,

Harris³

et al. 2016

JSHESS

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Climatology data of fire weather across the landscape can provide science-based evidence for informing strategic decisions to ameliorate the impacts (at times extreme) of bushfires on community socio-economic wellbeing and to sustain ecosystem health and functions. A long-term climatology requires spatial and temporal data that are consistent to represent the landscape in sufficient detail to be useful for fire weather studies and management purposes. To address this inhomogeneity problem for analyses of a variety of fire weather interests and to provide a dataset for management decision-support, a homogeneous 41-year (1972-2012), hourly interval, 4 km gridded climate dataset for Victoria has been generated using a combination of mesoscale modelling, global reanalysis data, surface observations, and historic observed rainfall analyses. Hourly near-surface forecast fields were combined with Drought Factor (DF) fields calculated from the Australian Water Availability Project (AWAP) rainfall analyses to generate fields of hourly fire danger indices for each hour of the 41-year period. A quantile mapping (QM) bias correction technique utilizing available observations during 1996-2012 was used to ameliorate any model biases in wind speed, temperature and relative humidity. Extensive evaluation was undertaken including both quantitative and case study qualitative assessments. The final dataset includes 4-km surface hourly temperature, relative humidity, wind speed, wind direction, Forest Fire Danger Index (FFDI), and daily DF and Keetch-Byram Drought Index (KBDI), and a 32-level full three-dimensional volume atmosphere.

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An observationally based evaluation of WRF seasonal simulations over the Central and Eastern Pacific

et al. 2015

J. Geophys. Res. Atmos.

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This study uses multiple satellite data sets to evaluate seasonal simulations of the Weather Research and Forecasting (WRF) model over Central and Eastern Pacific. Experiments with five different convective parameterizations all show reasonably good performance for precipitation simulations. However, large discrepancies exist in the model‐simulated ice clouds compared to CloudSat observations. Underestimations of ice clouds, mainly snow and graupel, are present in the Intertropical Convergence Zone (ITCZ) in all the experiments compared to CloudSat. In the ITCZ, all the experiments show a systematic overestimation of outgoing longwave radiation at the top of the atmosphere and downward shortwave radiation at the surface, along with biased cloud cooling in the middle and upper troposphere and biased cloud warming in the lower troposphere. Vertical motion is enhanced in the ITCZ compared to reanalysis. A weaker low‐level circulation over the midlatitude oceans is evidenced in all simulations with an eastward overextension of the South Pacific Convergence Zone and overestimated moisture over the Southern Hemisphere oceans when compared to Special Sensor Microwave/Imager observations. Sensitivity experiment demonstrates that doubling the radiative effect of snow can reduce high biases in vertical motion within the ITCZ and improve the large‐scale circulation and moisture over the midlatitude oceans.

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Sensitivity of WRF to driving data and physics options on a seasonal time-scale for the southwest of Western Australia

Cited by 62 publications

References 73 publications

An Analysis of Regional Climate Simulations for Western Australia’s Wine Regions—Model Evaluation and Future Climate Projections

An Analysis of Regional Climate Simulations for Western Australia’s Wine Regions—Model Evaluation and Future Climate Projections

A bias corrected WRF mesoscale fire weather dataset for Victoria, Australia 1972-2012

An observationally based evaluation of WRF seasonal simulations over the Central and Eastern Pacific

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